Grok 4.5 vs Gemini 3.1 Pro: Aggressive Price vs Multimodal Flagship (2026)

Grok 4.5 and Gemini 3.1 Pro are the two models compared here. Grok 4.5 is SpaceXAI's flagship reasoning model, generally available July 9, 2026, priced at $2.00 per million input tokens and $6.00 per million output tokens flat, with a 500,000-token context window, text-and-image input, and no availability in the European Union. Gemini 3.1 Pro is Google DeepMind's flagship, priced at $2 per million input tokens and $12 per million output for prompts up to 200,000 tokens, with a 1,000,000-token context window and native text, image, video, audio, and PDF input, available in the EU. This is a split verdict. Grok 4.5 leads on cheaper output, the independent Coding Agent Index (76, where Gemini is not charted), a lower cost per task, and flat pricing. Gemini 3.1 Pro leads on native multimodal input, a higher Artificial Analysis Intelligence Index (57 to 54), a charted LMArena Elo of 1485, double the context, and EU availability. Best for cheap output and coding value outside the EU: Grok 4.5. Best for native multimodal, intelligence, and EU access: Gemini 3.1 Pro.

Quick Verdict

This is a split verdict between SpaceXAI's aggressively priced flagship and Google's multimodal flagship, and neither wins outright — Grok 4.5 takes output price, coding value, and predictable billing, while Gemini 3.1 Pro takes native multimodality, aggregate intelligence, context, and EU availability. Grok 4.5 went generally available on July 9, 2026, three days before this comparison; Gemini 3.1 Pro has been Google's deployed flagship since February 2026 and sits in our production stack through Google AI Studio and Vertex AI. We have API access to both and have run them side by side, so we scope Grok's hands-on claims to roughly 72 hours of first impressions and lean on attributed third-party benchmarks — Artificial Analysis, LMArena, and vals.ai — wherever our own time is too short. Every figure below carries its source, and vendor claims are labeled as such. Here is the short version.

• Best on the independent agentic-coding leaderboard: Grok 4.5. Artificial Analysis scores it 76 on the Coding Agent Index; Gemini 3.1 Pro is not separately charted on that board, so Grok has the stronger independent agentic-coding signal here.
• Best on aggregate intelligence: Gemini 3.1 Pro. It scores 57 on the Artificial Analysis Intelligence Index against Grok's 54 — a three-point gap on the same index, with Grok sitting fourth behind the current frontier leaders.
• Best for output price: Grok 4.5, decisively. Its flat $6 per million output tokens is half of Gemini's $12 up to 200,000 tokens and a third of Gemini's $18 above that band. For output-heavy generation, this is the single biggest cost lever on the page.
• Best for cached-read price: Gemini 3.1 Pro. Its $0.20 per million cached input tokens up to 200,000 tokens undercuts Grok's flat $0.50, so cache-heavy workloads that replay large prompts pay less on Gemini.
• Best for native multimodal input: Gemini 3.1 Pro. It accepts native text, image, video, audio, and PDF; Grok 4.5 takes only text and image. For video and audio understanding in a single call, Gemini is the only option of the two.
• Best for long context: Gemini 3.1 Pro. Its 1,000,000-token context window is double Grok's 500,000, so book-length corpora and very large codebases fit in one call on Gemini where they may not on Grok.
• Best for predictable, flat pricing: Grok 4.5. Its $2 input and $6 output never change with prompt size, where Gemini carries a context-length surcharge above 200,000 tokens.
• Best for the lowest independent cost per task: Grok 4.5. Artificial Analysis puts its blended cost at roughly $2.49 per task on the Coding Agent Index; Gemini 3.1 Pro is not charted on that index, so there is no like-for-like independent figure against it.
• Best for human-preference evidence: Gemini 3.1 Pro. It is charted at 1485 on LMArena, where Grok 4.5 is absent — an availability of evidence rather than a proven quality gap.
• Best for availability: Gemini 3.1 Pro if you are in the European Union, where Grok 4.5 is not offered under the EU AI Act's systemic-risk designation. Outside the EU, both are reachable.

The honest caveats up front: Grok 4.5 has been public for three days, so we treat our hands-on notes as first impressions, not a settled verdict. The two vendors publish different benchmarks, so we compare only where the ground is solid. Neither model has an independently verified SWE-bench Verified score — Grok 4.5 is not yet on the independent vals.ai leaderboard, and Gemini's widely cited 80.6 percent is self-reported on DeepMind's model card, not run by vals.ai. Grok 4.5 is not charted on the LMArena Elo board that ranks Gemini, and Gemini is not on the Coding Agent Index that scores Grok. And SpaceXAI's own framing of Grok 4.5 as "Opus-class, much faster" is a vendor claim we label rather than adopt. We flag every one of those gaps rather than fill it.

Grok 4.5 vs Gemini 3.1 Pro — Overview

What Is Grok 4.5?

Grok 4.5 is the flagship reasoning model of SpaceXAI, generally available July 9, 2026 through the xAI API, and the successor to Grok 4.3 as the company's frontier model. We review it in depth in our Grok 4.5 review. Per SpaceXAI's model documentation, Grok 4.5 runs a 500,000-token context window, accepts text and image input to text output, and offers a reasoning-effort scale of low, medium, and high, with high as the default. It supports function calling and structured outputs, publishes rate limits of 150 requests per second and 50 million tokens per minute, and serves from the us-east-1 and us-west-2 regions. API pricing is a flat $2.00 per million input tokens, $0.50 per million cached input tokens, and $6.00 per million output tokens, with no long-context surcharge — xAI positions this as roughly half the price of rival flagships. Two facts frame the model. First, its founder Elon Musk describes it publicly as "Opus-class, much faster," a vendor claim we label and test against independent numbers rather than take at face value. Second, Grok 4.5 is not available in the European Union, which xAI attributes to the EU AI Act's systemic-risk designation — a neutral availability fact that matters if your users or data sit inside the EU.

What Is Gemini 3.1 Pro?

Gemini 3.1 Pro is Google DeepMind's flagship Gemini 3 series model, announced February 19, 2026 and still carrying the Preview label on its gemini-3.1-pro-preview model ID as of July 2026, even as it powers Google's frontier developer surfaces. We review it in depth in our Gemini 3.1 Pro review (our score: 9.0 out of 10). Per Google's model documentation and DeepMind's model card, it runs a 1,000,000-token input context with up to 64,000 output tokens and a January 2025 knowledge cutoff, and it accepts native multimodal input across text, image, video, audio, and PDF, returning text. It uses adaptive thinking shaped by an effort dial rather than an explicit extended-thinking flag, ships native Google Search and Maps grounding as first-party tools, and offers the widest first-party distribution of any frontier vendor — Google AI Studio, Vertex AI, the Gemini API and app, the Gemini CLI, Android Studio, and Antigravity. API pricing uses context-length tiering, which we verified directly on Google's pricing page: $2 per million input tokens and $12 output for prompts up to 200,000 tokens, rising to $4 and $18 above that. For the faster, cheaper sibling model, see our Gemini 3 Flash review.

How We Compared Them — and What We Did Not Do

Method transparency matters more than usual here, because Grok 4.5 is three days old at the time of writing and the two vendors publish different benchmarks that are easy to conflate. Here is exactly what we did and did not do, so you can weigh every claim below against its source. Our full methodology mirrors what we describe in our agentic coding model explainer.

• Pricing: both rate cards are vendor-verified at the source. Grok 4.5's flat $2.00 input and $6.00 output per million tokens is confirmed against SpaceXAI's model and pricing documentation; Gemini 3.1 Pro's tiered $2 and $12 (up to 200,000 tokens) is confirmed against Google's pricing page, including the higher $4 and $18 band above 200,000 tokens. No relayed figures.
• Independent benchmarks: we lean on Artificial Analysis (Intelligence Index, Coding Agent Index, and AA-Omniscience) and LMArena (Elo). We only declare a benchmark winner where both models were measured on the same suite under consistent conditions — and we say plainly when only one of them is charted.
• Data gaps we flag rather than fill: neither model appears on the independent vals.ai SWE-bench Verified board. Grok 4.5 is too new to be listed there; Gemini's 80.6 percent is self-reported on DeepMind's model card. Gemini is not separately charted on the Coding Agent Index that scores Grok at 76, and Grok is not on the LMArena board that lists Gemini at 1485. We do not substitute one model's number for the other's missing one.
• Vendor claims: SpaceXAI's "Opus-class, much faster" framing for Grok 4.5, and DeepMind's GPQA Diamond, ARC-AGI-2, and SWE-bench Verified numbers for Gemini, are labeled as vendor-reported and not treated as head-to-head evidence.
• Hands-on: we have run Gemini 3.1 Pro through Google AI Studio and Vertex AI on our content workflow since April 2026, and Grok 4.5 for roughly 72 hours since its July 9 GA, side by side on the same business tasks. That is enough for first impressions on Grok, not a controlled benchmark, and we scope every observation accordingly.
• Disclosure: we have no affiliate relationship with SpaceXAI or Google. There are no sponsored links on this page. Our team uses Gemini 3.1 Pro in production, which is exactly why we have held this comparison to independent, attributed numbers rather than our own habit.

Features and Benchmarks Comparison

The table below lists every dimension we could verify or attribute. Read the Winner column carefully: it distinguishes vendor-verified pricing, independent benchmarks, and vendor claims, and it marks a tie whenever the two are level or measured on different suites. A dash means the model is not charted on that board, which we treat as a data gap, not a zero.

Two symmetries stand out. Grok 4.5 owns the one independent agentic-coding board that scores it (the Coding Agent Index at 76, with a low $2.49 blended cost per task), where Gemini is absent; Gemini owns the one independent human-preference board that scores it (LMArena at 1485), where Grok is absent. And on aggregate intelligence the two are three points apart on Artificial Analysis, with Gemini ahead. This is why the verdict splits rather than crowning one model, and why we lean hard on each vendor's own documentation for the specification rows. The one row that rewards a careful read is factual reliability: Artificial Analysis flags Grok 4.5 with a 54 percent hallucination rate on its AA-Omniscience index, and Gemini 3.1 Pro is not charted there, so we present Grok's number as a documented caution rather than award Gemini a win it has no comparable score for.

Pricing Comparison

Pricing is where the two models diverge most cleanly, and both rate cards are vendor-verified. Grok 4.5 uses a single flat rate; Gemini 3.1 Pro tiers its rate by prompt size. We confirmed Grok on SpaceXAI's documentation and Gemini on Google's pricing page. For the plain-English version of what input, output, and cached tokens actually mean, see our AI model pricing explainer.

• Standard input: level at the common band. Grok 4.5 charges a flat $2 per million input tokens; Gemini 3.1 Pro charges the same $2 for prompts up to 200,000 tokens, then rises to $4 above that. So the two are identical on ordinary prompts, and Grok's flat rate becomes the cheaper of the two only on very large prompts above 200,000 tokens.
• Standard output: this is Grok 4.5's decisive win. Its flat $6 per million output tokens is half of Gemini's $12 up to 200,000 tokens and a third of Gemini's $18 above that. Because output tokens usually dominate the bill on generation-heavy work, this single line is the strongest cost argument on the page — a workload that emits far more than it ingests costs roughly half as much on Grok.
• Cached input: here Gemini 3.1 Pro turns the tables. It charges $0.20 per million cached input tokens up to 200,000 tokens (rising to $0.40 above) against Grok's flat $0.50, so workloads that replay large cached prompts — retrieval-augmented chat, long system prompts — pay less on Gemini. Note that Gemini adds a $4.50 per million tokens per hour cache-storage fee that Grok does not.
• Pricing predictability: Grok's flat card removes the tokenizer-and-tier math you otherwise have to run per request. Gemini's tiering means a prompt that crosses 200,000 tokens doubles its input rate and lifts output by half, so budgeting is a per-request calculation rather than a single number.
• Free access: Gemini offers free interactive testing through Google AI Studio but no free tier on the paid API. Grok 4.5 is an API and Grok-app model, with consumer access through the Grok app and X platform rather than a free developer tier.

The practical read: for output-heavy generation, Grok 4.5 is materially cheaper, and its flat card is the more predictable default. For cache-heavy workloads on ordinary prompt sizes, Gemini 3.1 Pro's cheaper cached reads and its identical $2 input make it competitive, and it stays cheaper on output only if you never look at the raw output line. On an independent basis, Artificial Analysis puts Grok's blended cost at roughly $2.49 per task on its Coding Agent Index; Gemini 3.1 Pro is not charted on that index, so there is no like-for-like independent cost-per-task figure to set against it.

Winner by Category

Because the two models are strong on different axes, the useful question is not which is better overall but which wins each job. Here is how the categories fall, with the source for each call.

• Agentic coding (independent): Grok 4.5. It scores 76 on the Artificial Analysis Coding Agent Index; Gemini 3.1 Pro is not charted there, so Grok has the only independent agentic-coding number of the two, at a low $2.49 blended cost per task.
• Output price: Grok 4.5. Flat $6 per million output tokens against Gemini's $12 to $18 is the biggest single cost gap on the page.
• Multimodal input: Gemini 3.1 Pro. Native video, audio, and PDF input in a single call is a capability Grok simply does not have — Grok is text and image in, text out.
• Aggregate intelligence: Gemini 3.1 Pro. 57 to 54 on the Artificial Analysis Intelligence Index, with Grok charted fourth behind the current frontier leaders.
• Context length: Gemini 3.1 Pro. Its 1,000,000-token window is double Grok's 500,000, so the largest corpora and codebases fit in one call where they may not on Grok.
• Human preference: Gemini 3.1 Pro on the record, because it is charted at 1485 on LMArena and Grok is not charted — an availability of evidence rather than a proven quality gap.
• Predictable billing: Grok 4.5. One flat rate at any prompt size, against Gemini's context-length tiers.
• Factual reliability: a caution on Grok. Artificial Analysis's AA-Omniscience index flags a 54 percent hallucination rate for Grok 4.5; Gemini 3.1 Pro has no comparable independent score, so we treat this as a documented reason to verify Grok's factual output, not as a Gemini win.
• Ecosystem depth: Gemini 3.1 Pro. The widest first-party distribution of any frontier vendor, from Vertex AI to Android Studio, plus native Google grounding.
• Regional availability: Gemini 3.1 Pro. It is available in the European Union, where Grok 4.5 is not offered under the EU AI Act's systemic-risk designation.

Pros and Cons

Grok 4.5 Pros and Cons

What we like about Grok 4.5

• Cheapest output of the two. Flat $6 per million output tokens, half or a third of Gemini's $12 to $18 — the strongest cost lever on generation-heavy work.
• Independent agentic-coding score. 76 on the Coding Agent Index, the only one of the two charted on that board, with a low $2.49 blended cost per task.
• Flat, predictable pricing. $2 input and $6 output per million tokens at any prompt size — no context-length surcharge to model.
• Generally available. A GA contract as of July 9, 2026, rather than a Preview label, with function calling and structured outputs at launch.
• Aggressive positioning. xAI prices it at roughly half of rival flagships, and its founder frames it as "Opus-class, much faster" — a vendor claim, but a signal of intent on speed and value.

Where Grok 4.5 falls short

• Text and image input only. No native video or audio, where Gemini accepts both — a hard gap for multimodal workloads.
• Half the context window. 500,000 tokens against Gemini's 1,000,000, so the very largest single-call corpora do not fit.
• Flagged hallucination rate. A 54 percent hallucination rate on the independent AA-Omniscience index, a documented reason to verify factual output.
• Not on the LMArena board and no independent SWE-bench score. Too new to be charted on either, so its strongest coding evidence is the Coding Agent Index alone.
• No EU availability and three days old. Blocked in the European Union, and public for roughly 72 hours at the time of writing, so its behavior over weeks is unproven.

Gemini 3.1 Pro Pros and Cons

What we like about Gemini 3.1 Pro

• Native multimodal input. Text, image, video, audio, and PDF in a single call — the clearest capability Grok cannot match.
• Double the context window. 1,000,000 tokens against Grok's 500,000, for book-length inputs and very large codebases in one call.
• Marginally higher aggregate intelligence. 57 on the Artificial Analysis Intelligence Index against Grok's 54, and charted at 1485 on LMArena.
• Native Google Search and Maps grounding. 5,000 free prompts per month, then $14 per 1,000 queries, for sourced answers without a retrieval pipeline.
• Deepest first-party distribution and EU availability. AI Studio, Vertex AI, Gemini CLI, Android Studio, and Antigravity, available in the European Union where Grok is not.

Where Gemini 3.1 Pro falls short

• Twice the output price on ordinary prompts. $12 per million output tokens up to 200,000 tokens against Grok's flat $6, rising to $18 above that band.
• Context-length surcharge. Prompts above 200,000 tokens cost more per token on both input and output, where Grok's rate never changes.
• Still a Preview model. Google's Preview label carries change-management risk, with a real shutdown precedent from March 2026.
• Older knowledge cutoff. A January 2025 cutoff means it leans on grounding for recent events, where a fresher model would not.
• Not on the AA Coding Agent Index. No independent agentic-coding-index number to weigh against Grok's 76.

When to Pick Grok 4.5 vs Gemini 3.1 Pro

Pick Grok 4.5 if...

• Your workload is output-heavy and cost-sensitive — flat $6 per million output tokens is half or a third of Gemini's rate.
• Your work is agentic coding measured on the AA Coding Agent Index, where Grok scores 76 and Gemini is not charted.
• You want one flat, predictable rate at any prompt size and would rather not model context-length tiers per request.
• You need a generally available contract rather than a Preview model that can change with limited notice.
• You operate outside the European Union and can add your own fact-checking layer to offset the flagged hallucination rate.

Pick Gemini 3.1 Pro if...

• Your inputs are multimodal — native video, audio, and PDF in a single call, which Grok cannot accept.
• You need the full 1,000,000-token context window for the largest corpora and codebases in one call.
• You want native Google Search and Maps grounding for sourced, up-to-date answers without building retrieval.
• Your stack is Google-native — AI Studio, Vertex AI, the CLI, Android Studio, or Antigravity give the shortest path to production.
• You operate in the European Union, where Grok 4.5 is not available, or you want the marginally higher aggregate-intelligence score and a charted human-preference Elo.

Frequently Asked Questions

Is Grok 4.5 better than Gemini 3.1 Pro in 2026?

It depends on the job, and we will not fake a single overall winner. Grok 4.5 leads where cost and coding value matter: its flat $6 per million output tokens is half of Gemini's $12, it scores 76 on Artificial Analysis's independent Coding Agent Index where Gemini 3.1 Pro is not charted, and its blended cost is a low $2.49 per task. Gemini 3.1 Pro leads on breadth: native multimodal input across text, image, video, audio, and PDF that Grok cannot match, a marginally higher Artificial Analysis Intelligence Index of 57 against 54, a charted LMArena Elo of 1485, double the context at 1,000,000 tokens, and availability in the European Union where Grok is not offered. Best for cheap output and coding value outside the EU: Grok 4.5. Best for native multimodal, intelligence, context, and EU access: Gemini 3.1 Pro.

How much do Grok 4.5 and Gemini 3.1 Pro cost?

Grok 4.5 costs $2 per million input tokens, $0.50 per million cached input tokens, and $6 per million output tokens, flat at any prompt size — we confirmed this on SpaceXAI's model documentation. Gemini 3.1 Pro uses context-length tiering, which we verified on Google's pricing page: for prompts up to 200,000 tokens it costs $2 per million input and $12 per million output; above 200,000 tokens it rises to $4 input and $18 output, with cached input at $0.20 and $0.40 per million respectively plus a $4.50 per million tokens per hour cache-storage fee. Input is level at the standard band ($2 each). On output Grok is decisively cheaper — half or a third of Gemini's rate. On cached reads Gemini is cheaper at $0.20 against Grok's flat $0.50. Both are reachable outside the EU; only Gemini is available inside it.

Which is better for coding: Grok 4.5 or Gemini 3.1 Pro?

On the one independent board that scores either, Grok 4.5 leads. Artificial Analysis ranks it 76 on the Coding Agent Index, while Gemini 3.1 Pro is not separately charted on that board. On SWE-bench Verified, the independent vals.ai leaderboard lists neither model directly — Grok 4.5 is too new to appear there, and Gemini's widely cited 80.6 percent comes from DeepMind's own model card, not an independent run. So the honest picture is: Grok has the stronger independent agentic-coding signal and a much cheaper output rate, Gemini has a published SWE-bench Verified number but a self-reported one, and neither has an independently verified SWE-bench Verified score on vals.ai. If you weight independent agentic-coding results and output cost, Grok leads; if you weight vendor model-card SWE-bench numbers, Gemini has one and Grok does not.

Why is Grok 4.5's SWE-bench score not listed here?

Because Grok 4.5 does not have an independently verified SWE-bench Verified score at the time of writing. It is too new to appear on the independent vals.ai leaderboard that runs the benchmark under controlled conditions, and we do not publish an unverified figure in its place. Gemini 3.1 Pro's widely cited 80.6 percent comes from DeepMind's own model card, not vals.ai, so we label it self-reported and never present it as third-party evidence. We keep independent and vendor-reported numbers strictly apart: Grok's verifiable coding evidence is its 76 on Artificial Analysis's Coding Agent Index, and Gemini's is its charted 1485 on LMArena. Anyone who tells you Grok 4.5 has a specific independent SWE-bench Verified percentage is citing a number that is not on the independent board.

Is Grok 4.5 really cheaper than Gemini 3.1 Pro?

On output, yes, decisively — and we verified both rate cards at the source. Grok 4.5's flat $6 per million output tokens is half of Gemini's $12 up to 200,000 tokens and a third of its $18 above that band. Since output tokens usually dominate the bill on generation-heavy work, a workload that emits far more than it ingests costs roughly half as much on Grok. The picture is more even elsewhere: input is identical at $2 per million on ordinary prompts, and on cached reads Gemini is actually cheaper at $0.20 against Grok's flat $0.50. So Grok is the cheaper model for output-heavy generation and for very large prompts, while Gemini is competitive on cache-heavy, ordinary-sized workloads. For raw output cost, Grok wins clearly; for cache-heavy retrieval workloads, Gemini can come out ahead.

Which has the larger context window: Grok 4.5 or Gemini 3.1 Pro?

Gemini 3.1 Pro, by a factor of two. Google's documentation lists Gemini 3.1 Pro at a 1,000,000-token input context with up to 64,000 output tokens and a January 2025 knowledge cutoff. SpaceXAI's documentation lists Grok 4.5 at a 500,000-token context window with text and image input. Both handle large documents and multi-file codebases, but Gemini's window is twice as large, so the very biggest single-call corpora — an entire large repository, a book plus its references — fit on Gemini where they may need chunking on Grok. If your workload routinely pushes past 500,000 tokens in one call, Gemini is the model of the two that can take it. If your prompts sit comfortably under that ceiling, Grok's 500,000 tokens is ample and comes with a much cheaper output rate.

What can Gemini 3.1 Pro do that Grok 4.5 cannot?

The clearest capability gap is native multimodal input. Gemini 3.1 Pro accepts text, image, video, audio, and PDF in a single call and returns text, which lets you drop a video walkthrough plus a slide deck into one prompt and get structured output. Grok 4.5 accepts only text and image input to text output. Gemini also ships native Google Search and Maps grounding as first-party tools (5,000 prompts per month free across the Gemini 3 family, then $14 per 1,000 queries), carries a 1,000,000-token context window that is double Grok's, and is available in the European Union where Grok 4.5 is not. It has the deepest first-party distribution of any frontier vendor, spanning Google AI Studio, Vertex AI, the Gemini CLI, Android Studio, and Antigravity. If your workload is multimodal extraction, retrieval-grounded answering, very-long-context work, or anything embedded in the Google Cloud stack, those are real Gemini advantages Grok does not match.

What can Grok 4.5 do that Gemini 3.1 Pro cannot?

Grok 4.5's differentiators are output price, coding value, flat billing, and GA status. Its flat $6 per million output tokens is half or a third of Gemini's rate, so output-heavy generation costs materially less. It carries an independent Artificial Analysis Coding Agent Index score of 76 at a low $2.49 blended cost per task, where Gemini is not charted on that board. Its pricing is flat at $2 input and $6 output per million tokens with no context-length surcharge, so billing is predictable at any prompt size. And Grok 4.5 is generally available as of July 9, 2026, whereas Gemini 3.1 Pro still carries Google's Preview label. Its founder frames it as "Opus-class, much faster," which we treat as a vendor claim pending independent latency benchmarks. For output-cost-sensitive generation, agentic-coding value, and predictable billing outside the EU, Grok has the edge.

Is Grok 4.5 multimodal?

Partly. Grok 4.5 accepts text and image input and produces text output. It does not support native audio or video input. For document work, its vision input covers scanned pages, charts, and screenshots, which covers many business tasks. If your workload requires native video or audio understanding in a single call, Gemini 3.1 Pro is the model of the two that can do it — it accepts text, image, video, audio, and PDF natively. So Grok is multimodal on input in a limited sense (text and image), while Gemini is fully multimodal on input. This is one of the clearest lines between the two: for anything involving native video or audio, Gemini is the only choice here, and for text-and-image work at a cheaper output rate, Grok is competitive.

Why is Grok 4.5 not available in the European Union?

SpaceXAI does not offer Grok 4.5 in the European Union, which it attributes to the EU AI Act's systemic-risk designation for the most capable general-purpose models. We present this as a neutral availability fact rather than a judgment on the model or the regulation: if your users, data, or company sit inside the EU, Grok 4.5 is not an option through the xAI API today, and Gemini 3.1 Pro — which is available in the EU and globally — is the model of the two you can deploy there. Outside the EU, both models are reachable through their respective APIs, and this comparison applies in full. For EU-based teams, the availability gap is decisive on its own, independent of any benchmark, because a model you cannot legally deploy cannot be part of your stack.

How reliable is Grok 4.5 on factual questions?

Independent data flags factual reliability as a Grok 4.5 weakness. On Artificial Analysis's AA-Omniscience index, Grok 4.5 scores 26 with a 54 percent hallucination rate — meaning it produces confident but incorrect answers on a majority of the index's hardest factual questions. Gemini 3.1 Pro is not charted on AA-Omniscience, so we cannot present a head-to-head number; we report Grok's figure as a documented caution rather than a comparative win for Gemini. The practical implication is that Grok 4.5's much cheaper output rate comes with a stronger case for a verification layer — retrieval grounding, citation checks, or human review — on any factual or high-stakes output. Gemini's answer to the same problem is its native Google Search and Maps grounding, which can supply sourced context at generation time and is one reason it is used in production on our own content workflow.

Can Grok 4.5 and Gemini 3.1 Pro work together in the same stack?

Yes, and a split stack is a rational setup given how differently they are strong. A practical routing pattern sends output-heavy generation and agentic coding measured on the Coding Agent Index to Grok 4.5, where the flat $6 output rate and the 76 coding score pay off, and sends multimodal work, very-long-context tasks, Google-grounded retrieval, and any EU-based deployment to Gemini 3.1 Pro, where it accepts native video and audio and is legally available. Abstraction layers such as the Vercel AI SDK, LangChain, or LiteLLM turn cost-and-capability routing by task type into a configuration exercise rather than a rewrite. Because the two lead on different axes — Grok on output cost and coding value, Gemini on modality, context, and reach — they are genuinely complementary, and many teams route by workload rather than standardizing on a single model. Just note that Grok is unavailable inside the EU, which forces Gemini for that region regardless of routing.

Final Verdict — A Split Between Cheap Output and Multimodal Breadth

After running both side by side, verifying pricing on both vendors' own documentation, and holding every capability claim to independent benchmarks, our verdict is a genuine split. Grok 4.5 is the cheap-output-and-coding-value pick: its flat $6 per million output tokens is half or a third of Gemini's rate, it scores 76 on the independent Coding Agent Index where Gemini is not charted, it carries a low $2.49 blended cost per task, and it prices flat with no context surcharge and ships as a generally available model. Gemini 3.1 Pro is the multimodal-breadth-and-reach pick: it accepts native video, audio, and PDF input that Grok cannot, scores marginally higher on aggregate intelligence at 57 to 54, is charted on LMArena at 1485 where Grok is absent, doubles the context window to 1,000,000 tokens, and is available in the European Union where Grok is not. We disclose plainly that our team runs Gemini 3.1 Pro in production — which is exactly why we anchored every capability comparison to third-party numbers rather than our own habit, and why we flag Grok's 54 percent hallucination rate on AA-Omniscience as a documented caution rather than bury it.

We did not crown a single overall winner because the evidence does not support one honestly. Grok wins the cost lines that matter most on generation-heavy work and the one independent coding board that scores it; Gemini wins the modality, context, intelligence, and availability lines that matter most on broad, multimodal, or EU-bound work. Each leads on the one independent board that scores it and is absent from the other's, and neither has an independently verified SWE-bench Verified score — so that argument is a wash. And SpaceXAI's "Opus-class, much faster" framing stays a vendor claim until independent latency benchmarks land. If your work is output-heavy generation, agentic coding, or anything that rewards predictable flat billing outside the EU — pick Grok 4.5. If your work is multimodal, very-long-context, Google-native, or EU-bound — pick Gemini 3.1 Pro. For most teams the rational endgame is routing by workload, because each model answers a question the other cannot. For the models one step away from this matchup, see our Grok 4.5 review, our Gemini 3.1 Pro review, our Claude Opus 4.8 review for the model Grok is measured against, and our related comparisons: Claude Opus 4.8 vs Gemini 3.1 Pro, Claude Sonnet 5 vs Gemini 3.1 Pro, and Claude Fable 5 vs Gemini 3.1 Pro.

Sources

Every figure in this comparison is attributed to a primary or independent source. Pricing and specifications come from the vendors' own documentation; capability scores come from independent third parties; vendor claims are labeled as such throughout.

• SpaceXAI — Grok 4.5 model documentation, specifications, and API pricing
• SpaceXAI (xAI) — Grok 4.5 announcement and positioning
• Google — Gemini API pricing (context-length tiers, verified)
• Google — Gemini 3.1 Pro model documentation
• Google DeepMind — Gemini 3.1 Pro model card (self-reported benchmarks)
• Artificial Analysis — Intelligence Index, Coding Agent Index, and AA-Omniscience
• LMArena — human-preference Elo leaderboard
• vals.ai — SWE-bench Verified independent leaderboard

Last compared: July 2026. Grok 4.5 reached general availability on July 9, 2026 and is not offered in the European Union; Gemini 3.1 Pro has been Google's deployed flagship since February 2026 and still carries a Preview label. Both models are moving fast, and we will revise this comparison as independent benchmark coverage matures.